Open In App
Related Articles

How to use Function Decorators in Python ?

Improve
Improve
Improve
Like Article
Like
Save Article
Save
Report issue
Report

In Python, a function can be passed as a parameter to another function (a function can also return another function). we can define a function inside another function. In this article, you will learn How to use Function Decorators in Python.

Passing Function as Parameters

In Python, you can pass a function as an argument to another function, just like you would pass any other data type (e.g., integers, strings). This allows you to create more flexible and reusable code because you can write functions that take other functions as input, allowing you to customize the behaviour of the higher-order function.

Python3

def apply(func, value):
    return func(value)
 
def square(x):
    return x ** 2
 
result = apply(square, 5)
print(result)  # Output: 25

                    

Output
25

Using @ function

A decorator is a function that takes a function as its only parameter and returns a function. This is helpful to “wrap” functionality with the same code over and over again. For example, the above code can be rewritten as follows. We use @func_name to specify a decorator to be applied to another function. 

Python

# Adds a welcome message to the string
# returned by fun(). Takes fun() as
# parameter and returns welcome().
def decorate_message(fun):
 
    # Nested function
    def addWelcome(site_name):
        return "Welcome to " + fun(site_name)
 
    # Decorator returns a function
    return addWelcome
 
@decorate_message
def site(site_name):
    return site_name;
 
# Driver code
 
# This call is equivalent to call to
# decorate_message() with function
# site("GeeksforGeeks") as parameter
print site("GeeksforGeeks")

                    

Output:

Welcome to GeeksforGeeks

Attaching Data to Functions

Decorators can also be useful to attach data (or add attribute) to functions. 

Python

# A Python example to demonstrate that
# decorators can be useful attach data
 
# A decorator function to attach
# data to func
def attach_data(func):
       func.data = 3
       return func
 
@attach_data
def add (x, y):
       return x + y
 
# Driver code
 
# This call is equivalent to attach_data()
# with add() as parameter
print(add(2, 3))
 
print(add.data)

                    

Output:

5
3

‘add()’ returns sum of x and y passed as arguments but it is wrapped by a decorator function, calling add(2, 3) would simply give sum of two numbers but when we call add.data then ‘add’ function is passed into then decorator function ‘attach_data’ as argument and this function returns ‘add’ function with an attribute ‘data’ that is set to 3 and hence prints it. Python decorators are a powerful tool to remove redundancy. Please refer Decorators in Python for more det

Using add function

Here is an example to represent the use of add function in decorators.

In the code above, log_decorator is the decorator function that takes the add function as an argument. It returns a new function called wrapper, which adds logging before and after calling add. The @log_decorator syntax is a shorthand way of applying the log_decorator function to the add function. When we call add, the logging statements will be printed to the console.

Python3

def log_decorator(func):
    def wrapper(*args, **kwargs):
        print(f"Calling {func.__name__} with args={args} kwargs={kwargs}")
        result = func(*args, **kwargs)
        print(f"{func.__name__} returned {result}")
        return result
    return wrapper
 
@log_decorator
def add(a, b):
    return a + b
 
result = add(2, 3)

                    

Output
Calling add with args=(2, 3) kwargs={}
add returned 5

Time complexity : O(1)

Auxiliary Space : O(n)



Last Updated : 11 Oct, 2023
Like Article
Save Article
Previous
Next
Share your thoughts in the comments
Similar Reads